EMG Driven Model of the Lumbar Spine during Flexion, Bending and Rotation Using Opensim

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Title: EMG Driven Model of the Lumbar Spine during Flexion, Bending and Rotation Using Opensim
Authors: Curtin, MauriceMcManus, Lara M.McCarty Persson, UlrikLowery, Madeleine M.
Permanent link: http://hdl.handle.net/10197/8211
Date: 9-Aug-2013
Online since: 2016-12-12T12:49:05Z
Abstract: This study utilised the OpenSim platform to develop an EMG driven model of the lumbar spine by expanding an existing model and incorporating a plugin to represent intervertebral stiffness. Subject-specific kinematic data and surface EMG activity were recorded from 4 subjects during flexion and extension, lateral bending, and axial rotation. The model was used to predict muscle excitation patterns necessary to produce the recorded motions, and the patterns were compared with the recorded EMG data. The model was then driven with the recorded EMG data, and new excitation patterns were calculated for the deep muscles for which EMG data was not available. Simulations were conducted for intervertebral lumbar stiffness corresponding to preloading of 0N, 250N and 500N. The model-predicted excitation patterns were most comparable to recorded EMG data for the flexion and extension motions. Excitation levels predicted for all motions were sensitive to the applied preload. Although activation patterns remained similar, there was a substantial variation in model-predicted muscle excitation levels with change in intervertebral stiffness.
Type of material: Conference Publication
Keywords: Personal sensingMuscle architectureIntervertebral stiffnessModelling
Other versions: http://www.isbbrazil.com/
Language: en
Status of Item: Peer reviewed
Conference Details: ISB 2013: XXIV Congress of the International Society of Biomechanics; XV Brazilian Congress of Biomechanics, Natal, Rio Grande do Norte, Brazil, 4-9 August 2013
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Electrical and Electronic Engineering Research Collection
Public Health, Physiotherapy and Sports Science Research Collection
Insight Research Collection

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